Artificial Intelligence
Fine-tune OpenAI GPT-OSS models on Amazon SageMaker AI using Hugging Face libraries
Released on August 5, 2025, OpenAI’s GPT-OSS models, gpt-oss-20b and gpt-oss-120b, are now available on AWS through Amazon SageMaker AI and Amazon Bedrock. In this post, we walk through the process of fine-tuning a GPT-OSS model in a fully managed training environment using SageMaker AI training jobs.
Optimize hosting DeepSeek-R1 distilled models with Hugging Face TGI on Amazon SageMaker AI
In this post, we demonstrate how to optimize hosting DeepSeek-R1 distilled models with Hugging Face Text Generation Inference (TGI) on Amazon SageMaker AI.
Explore data with ease: Use SQL and Text-to-SQL in Amazon SageMaker Studio JupyterLab notebooks
Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. In the process of working on their ML tasks, data scientists typically start their workflow by discovering relevant data sources and connecting to them. They then use SQL to explore, analyze, visualize, and integrate […]
Boost productivity on Amazon SageMaker Studio: Introducing JupyterLab Spaces and generative AI tools
Amazon SageMaker Studio offers a broad set of fully managed integrated development environments (IDEs) for machine learning (ML) development, including JupyterLab, Code Editor based on Code-OSS (Visual Studio Code Open Source), and RStudio. It provides access to the most comprehensive set of tools for each step of ML development, from preparing data to building, training, […]
Unlocking efficiency: Harnessing the power of Selective Execution in Amazon SageMaker Pipelines
MLOps is a key discipline that often oversees the path to productionizing machine learning (ML) models. It’s natural to focus on a single model that you want to train and deploy. However, in reality, you’ll likely work with dozens or even hundreds of models, and the process may involve multiple complex steps. Therefore, it’s important […]




